Predicting the profit of 50 startups depending on their r&d spend location etc.

After linear regression, I decided to make multiple linear regression model which will make prediction by learning from different multiple features. The following project uses the dataset of 50 startups and we have to predict their profits. The code has been written in such a way that it can be tweaked to work with other models as well. I have used pandas library to read dataset and numpy for vectorisation. Sklearn is used to generate test and train data. There is one categorical feature in the data so i have encoded it using one hot encoder. Normalisation was really necessary in this case as data values were very large. I needed to avoid dummy variable trap that is why I deleted the first column generated by one hot encoder.